CASE: A Framework for Computer Supported Outbreak Detection

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Cakici, Baki; Hebing, Kenneth; Grünewald, Maria; Saretok, Paul and Hulth, Anette. 2010. CASE: A Framework for Computer Supported Outbreak Detection. BMC Medical Informatics & Decision Making, 10(14), ISSN 1472-6947 [Article]

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Abstract or Description

Background: In computer supported outbreak detection, a statistical method is applied to a collection of cases to detect any excess cases for a particular disease. Whether a detected aberration is a true outbreak is decided by a human expert. We present a technical framework designed and implemented at the Swedish Institute for Infectious Disease Control for computer supported outbreak detection, where a database of case reports for a large number of infectious diseases can be processed using one or more statistical methods selected by the user.

Results: Based on case information, such as diagnosis and date, different statistical algorithms for detecting outbreaks can be applied, both on the disease level and the subtype level. The parameter settings for the algorithms can be configured independently for different diagnoses using the provided graphical interface. Input generators and output parsers are also provided for all supported algorithms. If an outbreak signal is detected, an email notification is sent to the persons listed as receivers for that particular disease.

Conclusions: The framework is available as open source software, licensed under GNU General Public License Version 3. By making the code open source, we wish to encourage others to contribute to the future development of computer supported outbreak detection systems, and in particular to the development of the CASE framework

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Article

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https://doi.org/10.1186/1472-6947-10-14